A variety of methods are known for detecting behavior-based associations (associations based on user behaviors) among items stored or represented in a database. For example, the purchase histories or item viewing histories of users may be analyzed to detect behavior-based associations between particular items represented in an electronic catalog (e.g., items A and B are related because a relatively large number of those who purchased A also purchased B). As another example, the network browsing histories of users may be analyzed to identify behavior-based associations between particular network sites and/or network pages.
The detected behavior-based associations may be used to assist users in locating items of interest. For example, in the context of an electronic catalog, when a user accesses a network resource, such as a network page, that is associated with an item, the resource may be supplemented with a list of related items. This list may, for example, be preceded with a descriptive message such as “people who bought this item also bought the following,” or “people who viewed this item also viewed the following.” The detected associations may also be used to generate personalized recommendations that are based on the target user's purchase history, item viewing history, search related behaviors, and/or other item selections.